Dolphin (Document Image Parsing via Heterogeneous Anchor Prompting) is a novel multimodal document image parsing model that follows an analyze-then-parse paradigm. It addresses the challenges of complex document understanding through a two-stage approach designed to handle intertwined elements such as text paragraphs, figures, formulas, and tables.
Document image parsing is challenging due to its complexly intertwined elements such as text paragraphs, figures, formulas, and tables. Dolphin addresses these challenges through a two-stage approach:
🔍 Stage 1: Comprehensive page-level layout analysis by generating element sequence in natural reading order
🧩 Stage 2: Efficient parallel parsing of document elements using heterogeneous anchors and task-specific prompts
Dolphin achieves promising performance across diverse page-level and element-level parsing tasks while ensuring superior efficiency through its lightweight architecture and parallel parsing mechanism.
@inproceedings{dolphin2025,
title={Dolphin: Document Image Parsing via Heterogeneous Anchor Prompting},
author={Feng, Hao and Wei, Shu and Fei, Xiang and Shi, Wei and Han, Yingdong and Liao, Lei and Lu, Jinghui and Wu, Binghong and Liu, Qi and Lin, Chunhui and Tang, Jingqun and Liu, Hao and Huang, Can},
year={2025},
booktitle={Proceedings of the 65rd Annual Meeting of the Association for Computational Linguistics (ACL)}
}
